1  7
2. Time series analysis [2008]
 Madsen, Henrik, 1955
 Boca Raton : Chapman & Hall/CRC, ©2008
 Description
 Book — 1 online resource (372 pages) : illustrations
 Summary

 Multivariate random variables
 Regressionbased methods
 Linear dynamic systems
 Stochastic processes
 Identification, estimation, and model checking
 Spectral analysis
 Linear systems and stochastic processes
 Multivariate time series
 State space models of dynamic systems
 Recursive estimation
 Real life inspired problems
 Appendix A : the solution to difference equations
 Appendix B : partial autocorrelations
 Appendix C : some results from trigonometry
 Heclo, Hugh.
 Philadelphia : Temple University Press, c1987.
 Description
 Book — xi, 348 p. : ill. ; 22 cm.
 Online
4. Statistics for finance [2015]
 Lindström, Erik, author.
 Boca Raton, FL : CRC Press, [2015]
 Description
 Book — 1 online resource (1 volume) : illustrations
 Summary

 Introduction Introduction to financial derivatives Financial derivativeswhat's the big deal? Stylized facts Overview
 Fundamentals Interest rates Cash flows Continuously compounded interest rates Interest rate options: caps and floors
 DiscreteTime Finance The binomial one period model The one period model The multi period model
 Linear Time Series Models Introduction Linear systems in the time domain Linear stochastic processes Linear processes with a rational transfer function Autocovariance functions Prediction in linear processes
 NonLinear Time Series Models Introduction The aim of model building Qualitative properties of the models Parameter estimation Parametric models Model identification Prediction in nonlinear models Applications of nonlinear models
 Kernel Estimators in Time Series Analysis Nonparametric estimation Kernel estimators for time series Kernel estimation for regression Applications of kernel estimators
 Stochastic Calculus Dynamical systems The Wiener process Stochastic Integrals Ito stochastic calculus Extensions to jump processes
 Stochastic Differential Equations Stochastic differential equations Analytical solution methods FeynmanKac representation Girsanov measure transformation
 ContinuousTime Security Markets From discrete to continuous time Classical arbitrage theory Modern approach using martingale measures Pricing Model extensions Computational methods
 Stochastic Interest Rate Models Gaussian onefactor models A general class of onefactor models Timedependent models Multifactor and stochastic volatility models
 The Term Structure of Interest Rates Basic concepts The classical approach The term structure for specific models HeathJarrowMorton framework Credit models Estimation of the term structurecurvefitting
 DiscreteTime Approximations Stochastic Taylor expansion Convergence Discretization schemes Multilevel Monte Carlo Simulation of SDEs
 Parameter Estimation in Discretely Observed SDEs Introduction High frequency methods Approximate methods for linear and nonlinear models State dependent diffusion term MLE for nonlinear diffusions Generalized method of moments (GMM) Model validation for discretely observed SDEs
 Inference in Partially Observed Processes Introduction The model Exact filtering Conditional moment estimators Kalman filter Approximate filters State filtering and prediction The unscented Kalman filter A maximum likelihood method Sequential Monte Carlo filters Application of nonlinear filters
 Appendix A: Projections in Hilbert Spaces Appendix B: Probability Theory
 Bibliography
 Problems appear at the end of each chapter.
 (source: Nielsen Book Data)
(source: Nielsen Book Data)
5. Fremad March! [electronic resource]. [2004]
 Denmark : Classico, [2004]
 Description
 Music recording — 1 online resource.
 Summary

 For kong, folk og Land / E. Hass
 1st Livgarde Bataljon march / Christian Aage Bruun
 Christiansborg march / Hans Madsen
 Gatchina march / Nicolai Ferdinand Hoyer
 March danoise / Axel Frederiksen
 2nd Livgarde Bataljon march / Christian Aage Bruun
 Dansk honnormarch / Carl Olsen
 Dronning Olga march / Christian Florus Dahl
 Slagelse tappenstreg / Ludwig Makwarth
 Sangermarch / Jacob Schou Ernst
 12th Bataljons 200 Ars Jubilaeumsmarch / Julius Bergmann
 Jyske Flyveafdelings march / Aage V. Beyer
 MacMahon march / Hans Christian Lumbye
 Nu kommer garden / Christian Larsen
 Jubilaeumsmarch / Nicolai Ferdinand Hoyer
 March til 8th Regiment / Julius Bergmann
 Nu kommer Garden / Ludwig Makwarth
 Nu kommer Garden / Christian Larsen
 Ungarsk Husarmarch / Carl Christian Moller
 Orlogsmarch / Richard Lindebro.
6. Statistics for Finance [2015]
 Lindstrom, Erik, author.
 First edition.  Boca Raton, FL : Chapman and Hall/CRC, [2018].
 Description
 Book — 1 online resource (384 pages) : 74 illustrations, text file, PDF.
 Summary

 IntroductionIntroduction to financial derivatives Financial derivativeswhats the big deal? Stylized factsOverview  Fundamentals Interest rates Cash flows Continuously compounded interest rates Interest rate options: caps and floors  DiscreteTime Finance The binomial one period model The one period model The multi period model  Linear Time Series Models Introduction Linear systems in the time domain Linear stochastic processes Linear processes with a rational transfer functionAutocovariance functions Prediction in linear processes  NonLinear Time Series Models Introduction The aim of model buildingQualitative properties of the models Parameter estimationParametric models Model identification Prediction in nonlinear models Applications of nonlinear models  Kernel Estimators in Time Series Analysis Nonparametric estimation Kernel estimators for time series Kernel estimation for regression Applications of kernel estimators Stochastic Calculus Dynamical systems The Wiener process Stochastic Integrals It stochastic calculus Extensions to jump processes  Stochastic Differential Equations Stochastic differential equations Analytical solution methods FeynmanKac representation Girsanov measure transformation  ContinuousTime Security Markets From discrete to continuous time Classical arbitrage theoryModern approach using martingale measures Pricing Model extensions Computational methods  Stochastic Interest Rate Models Gaussian onefactor models A general class of onefactor models Timedependent models Multifactor and stochastic volatility models  The Term Structure of Interest Rates Basic concepts The classical approach The term structure for specific models HeathJarrowMorton framework Credit models Estimation of the term structurecurvefitting  DiscreteTime Approximations Stochastic Taylor expansionConvergence Discretization schemes Multilevel Monte Carlo Simulation of SDEs  Parameter Estimation in Discretely Observed SDEsIntroduction High frequency methods Approximate methods for linear and nonlinear modelsState dependent diffusion term MLE for nonlinear diffusionsGeneralized method of moments (GMM) Model validation for discretely observed SDEs  Inference in Partially Observed Processes IntroductionThe model Exact filtering Conditional moment estimators Kalman filter Approximate filters State filtering and predictionThe unscented Kalman filter A maximum likelihood method Sequential Monte Carlo filters Application of nonlinear filters  Appendix A: Projections in Hilbert Spaces Appendix B: Probability Theory  Bibliography Problems appear at the end of each chapter.
(source: Nielsen Book Data)
7. Energy Systems Integration. Defining and Describing the Value Proposition [electronic resource] [2016]
 Washington, D.C. : United States. Dept. of Energy. ; Oak Ridge, Tenn. : distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2016
 Description
 Book — 12 p. : digital, PDF file.
 Summary

This white paper defines the concept and value proposition of energy systems integration (ESI) for the International Institute of Energy Systems Integration (iiESI).
 Online
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